P696 Design and rationale for the multicentre, randomised, controlled VERDICT trial to determine the optimal treatment target in patients with ulcerative colitis
Bibliographic record
Abstract
Abstract Background Symptoms, endoscopy, histology, and biomarkers are used to evaluate disease activity and response to therapy in ulcerative colitis (UC). Histologic disease activity may persist in ~25% of patients with normal-appearing endoscopic mucosa, and observational studies demonstrate an association between the achievement of histologic remission (vs endoscopic remission alone) and a lower risk of complications. These findings suggest that histologic remission may be a distinct treatment target. The aim of the VERDICT trial is to determine the optimal treatment target in UC to inform clinical practice and future drug development. Methods The primary objective of the multicentre, randomised, controlled VERDICT trial (Figure 1) is to determine whether a treatment target of corticosteroid (CS)-free symptomatic + endoscopic + histologic remission is superior to CS-free symptomatic remission alone in moderately to severely active UC (Mayo rectal bleeding subscore [RBS] ≥1; Mayo endoscopic score [MES] ≥2). Patients are randomised to 3 treatment targets (2:3:5 ratio): CS-free symptomatic remission (Mayo RBS = 0) (Group 1); CS-free endoscopic remission (MES ≤1) + symptomatic remission (Group 2); or CS-free histologic remission (Geboes score <2B.0) + endoscopic remission + symptomatic remission (Group 3). Therapy is administered according to a treatment algorithm that is dependent on each patient’s existing UC treatment regimen at study entry (Figures 2-4). Early introduction of vedolizumab and dose escalation to a maximum of 300 mg every 4 weeks until the assigned treatment target is reached are central to each algorithm. There are 3 opportunities, 16 weeks apart (weeks 16, 32, or 48), to achieve the treatment target. Urine, stool, mucosa, and serum samples are collected at these follow-up time points and at baseline for subsequent biomarker and prediction model development. Results The primary efficacy outcome is the time from treatment target achievement to a UC-related complication, defined as a UC-related hospitalisation, colectomy, need for rescue therapy, or treatment-related or other complication. This composite outcome will be compared among treatment target Groups 1 and 3 using the Cox proportional hazard model analysis. The trial was initiated in September 2020, and 660 patients are planned for enrolment. Of these, ~50% are currently enrolled at 55 sites across 10 North American and European countries. Prespecified interim analyses will be conducted when the first 50 patients in each group reach weeks 16, 32, and 48. Conclusion The VERDICT trial in active UC is designed to determine the optimal treatment target to inform clinical practice, drug trials, and future evidence-based recommendations.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.049 | 0.042 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.004 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.015 | 0.003 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".